The IEEE 802.15.4 [1] standard targets low data rate wireless networks with extensive battery life and very low complexity. Its physical layer is based on a narrowband radio, operating in the unlicensed ISM band around 2.4 GHz. IEEE 802.15.4a [2] is an amendment to the 802.15.4 specification. It adds an impulse-radio ultra-wide band (IR-UWB) physical layer operating in several bands of 500 MHz (and 1.5 GHz) from approximately 3 GHz to 10 GHz. This physical layer should offer a better robustness against interference and multipath propagation channels, a higher data rate, and the possibility to perform ranging between devices.
As it is the case in several modern (wireless) communication networks, information exchange in IEEE 802.15.4 is packet based. The bits to be sent are grouped into packets that are sent individually from the transmitter to the receiver over the wireless medium. In order to retrieve the bits from a packet, a receiver has to perform a certain number of tasks. First, the receiver has to actually detect the presence of the packet and subsequently determine where this packet begins. This process is commonly referred to as “packet detection and timing acquisition” or “synchronization”. It generally relies on the presence of a so called “preamble” appended before the payload (the data bits). This preamble is known in advance to the receiver. Once synchronization is achieved, the receiver knows where to look for the unknown payload and can perform “demodulation and decoding” to recover it. Often, the receiver also performs a “channel estimation” step between synchronization and decoding to gain some knowledge about the statistics of the communication channel. This knowledge is then used to enhance the performance of demodulation and decoding.
Networks such as IEEE 802.15.4 networks are asynchronous networks. There is no common reference clock in the system. Rather, every device has its own free running clock. Furthermore, because the design objective of IEEE 802.15.4 devices is low-cost, low-power and low complexity, high precision oscillators cannot be used to generate the clock on these devices. Cheap oscillators available today have a precision of about ±20 ppm (parts per million). This implies that the clocks of two devices do not run at the exact same speed and their frequencies may thus differ slightly; after some time these clocks drift apart from each other. Consequently, in an asynchronous network with free running clocks, packet detection and timing acquisition has to be obtained for every packet individually. In addition, even within a packet, a mechanism (“clock offset tracking”) is needed to maintain synchronization and compensate for clock drifts between a transmitter and a receiver. In IEEE 802.15.4a, synchronization and clock offset tracking are especially challenging because the fine temporal resolution of UWB signals requires high timing accuracies. Further, IR-UWB signals lack a continuous sinusoidal carrier. Therefore, classical solutions to address clock-offset issues in narrowband systems, such as phase-locked loops (PLL), cannot be used, since these methods require the presence of a continuous sinusoidal signal.
Finally, with more and more dense wireless networks emerging and being deployed, multi-user interference (MUI) between devices of the same network or neighboring networks starts to severely limit the network performance. It is therefore highly desirable that a receiver performs all the tasks needed to receive a packet in such a way as to limit the impact of MUI as much as possible.
Patent applications [10], [11] are, addressing ranging applications. In particular, they concentrate on the estimation of the time of arrival (TOA). The techniques proposed in [10], [11] construct an energy matrix for the problem of TOA estimation in ranging applications. These two patents contain:                the construction of an energy matrix from the output of a non coherent receiver;        the application of image analysis or pattern recognition techniques to the energy matrix;        the application of a leading edge detection algorithm on the matrix to find the TOA or the first multi-path channel tap;        the detection and removal of interference based on the energy matrix, plus the likelihood histogram concepts;        hypothesis testing to determine whether a certain column in the matrix corresponds to noise or useful signal;        
These two patents do not contain the following elements:                any notion of angle in the energy matrix that can be used to detect clock frequency offsets. It even explicitly states that “It is important to note that received energies always form a straight column or row . . . ”;        a single word on channel estimation;        a single word on combining different multi-path components for synchronization or TOA estimation. They are always only concerned with leading edge detection;        anything about thresholding the matrix to reject interference;        anything about transforming/compressing the energy matrix to reduce the memory requirement;        anything about the Radon or the Hough transform.        
The concept of energy matrix, appears in [7], [6] where the output of an energy detector is represented in matrix form. The matrix is processed with filters known from image processing in order to reject narrowband and wideband interference. In both papers, the thresholds are only used to detect the arrival of the first path but not to reject interference terms. The filters described, especially the differential filter in [7], are well-known filters from image processing and may also be applied to the energy matrix of the present invention prior to transformation in order to enhance edge features.
The Hough transform as well as the more general Radon transform are well-established techniques from computer vision and image processing. The Hough transform, for example, goes back to a patent from 1962 [12] and the ρ, θ parameterization used widely today goes back to a paper published in 1972 [8]. Since then, there has been a large body of literature as well as patents related to the Radon/Hough transform. Most of these publications relate to applications requiring classical pattern recognition task in images (for example in computer tomography or radar applications) or they deal with ways to compute the transforms and their inverses in efficient ways. No document was found that proposes to use the Radon/Hough transform in any form in a radio communication receiver in general and for clock drift estimation or synchronization in particular.
Patent application [13] and the corresponding paper [14], describe a maximum likelihood estimator for clock drift estimation in a coherent or non-coherent IR-UWB low data-rate (LDR) receiver. Only clock drift estimation assuming perfect synchronization and channel estimation is treated. Several samples from the receiver are accumulated and yield nodes of a trellis on which the best path is calculated to yield the maximum likelihood estimate. Tracking and compensating for the drift is not treated, neither is it explained how to achieve synchronization and channel estimation.
Patent application [4] and its companion paper [15] contain a synchronization method that is robust to MUI. The method is for the synchronization of coherent receivers and has no notion of energy matrix whatsoever. However, its basic principle for rejecting interference, which is the proposed power independent detection method, can be applied to the received signal prior to placing it in the energy matrix and transforming it via the Radon/Hough transform in order to reject interference.
Patent application [3] and the corresponding conference paper [16] contain methods to reject interference in a non-coherent IR-UWB receiver. The methods described therein can be used for interference mitigation also during the clock offset tracking method once the channel estimation has been performed.